Download A High-Performance Stand-Alone Solar PV Power System for LED

Hindawi Publishing Corporation
ISRN Renewable Energy
Volume 2013, Article ID 573919, 10 pages
http://dx.doi.org/10.1155/2013/573919
Research Article
A High-Performance Stand-Alone Solar PV Power
System for LED Lighting
José António Barros Vieira1 and Alexandre Manuel Mota2
1
Escola Superior de Tecnologia de Castelo Branco, Unidade Técnico Cientifica de Engenharia Electrotécnica e Industrial,
Avenida Empresário, 6000 Castelo Branco, Portugal
2
Departamento de Electrónica Telecomunicações e Informática, Universidade de Aveiro, 3810 Aveiro, Portugal
Correspondence should be addressed to José António Barros Vieira; [email protected]
Received 19 April 2013; Accepted 11 June 2013
Academic Editors: O. Badran and M. Beccali
Copyright © 2013 J. A. B. Vieira and A. M. Mota. This is an open access article distributed under the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.
This paper presents new improvements and real result of a stand-alone photovoltaic power system for LED lighting that was
developed previously. The actual system, during day, charges a lead acid battery using MPPT algorithm for power transfer
optimization, and, during night, it supervises battery discharge and controls the current in the power LED array. The improvements
are in hardware and software. The hardware was simplified using only one DC/DC converter and only one microcontroller making
it more efficient. The system board uses an ATMEL ATTINY861V microcontroller, a single-ended primary inductance converter
(SEPIC), and sensors to read input and output voltages and currents to control all system. The software improvements are made in
the battery charging algorithm, battery discharging algorithm, and in current control of the power LED array adjusting the light
intensity. Moreover, results are presented showing the balance of energy in a period of 24 hours: first results of the MPPT algorithm
in bulk battery charge phase and then the over battery charge phase, both in a sunny day. The power LED current control results
are also presented showing a very small error. It turns off at 00 : 00 at each day to reduce the waste of energy. Finally, the balance of
energy is studied and presented to help the right projection of the PV power panel needed and the necessary battery capacity.
1. Introduction
The use of stand-alone photovoltaic lighting system has
increased in remote rural areas and in towns. Conventional
street lighting is energy intensive and can represent a high
cost to local governments, which creates an impetus to
investigate more efficient light sources such as photovoltaic(PV-) powered light emitting diodes (PLEDs) lighting systems. Photovoltaic system is gaining increased importance
as a renewable source due to its advantages such as little
maintenance and no noise and wear due to its absence
of moving parts. But there are still two principal barriers
to the generalization use of photovoltaic systems: the high
installation cost and the low energy conversion efficiency.
To increase the ratio output power/cost of installation it is
important that PV panel operates in its maximum power
point (MPP) to absorb the maximum power possible. The
combination of PV panels with power LEDs makes the called
new green light sources.
Battery is the energy store element in this system. State
measure and energy management are critical issues for the
battery in PV LED lighting system, such as the state of charge
(SOC) [1].
(1) The fast charging capability may not be obtained because of the weather uncertainty.
(2) The charge time is limited by the sunshine time every
day.
(3) Under charging usually happens to shorten the battery life since the PV panel size is limited by economy
consideration.
The battery charge and discharge processes should be
made correctly to enlarge its durability maximizing the stored
energy [2, 3]. To reduce the PV panel size it is important to
maximise the power transference from PV panel to battery
using some maximum power point tracker (MPPT) like the
Perturbation and Observation (P&O) algorithm [4–6]. P&O
2
algorithm is a very popular algorithm duo to its simplicity,
convergent capacities, and to its low computational needs.
To create light with good yield the LED is the best option,
it has been widely used and investigated having many advantages: high luminous efficiency, low environment pollution,
long life, and firmness. LED lighting system supplied by
batteries is one of most popular solutions to home, public
lighting, vehicle, and signalizing lighting system [5–12].
Autonomous LED lighting system consists in three major
parts: batteries, lighting controller module, and LED array
module. Boost DC/DC converter is usually used as main
circuit of the lighting controller module [5, 9]. It is not
easy to control the brightness of LED lighting system, due
to its nonlinearity electrical characteristics, and temperature
sensitivity [5, 9]. In [9], it is refereed that constant voltage
control has disadvantages relatively to constant current control. However, conventional simple constant current control
strategy may cause overcurrent and overheats if the control
algorithm ignores LED temperature characteristics [9].
This work proposes an intelligent, economic, and efficient
system to control a stand alone photovoltaic lighting system.
It presents improvements in charging algorithm, in particular
in P&O algorithm, improvements in monitoring the battery
discharge, and in LED array current control algorithm. These
improvements will considerably improve the stand alone
photovoltaic lighting results.
During day, the battery is charged using the photovoltaic
panel energy and, during night, the power LED brightness
is controlled with the PI algorithm always supervising the
battery discharge energy consumption. This is the first work
that makes such a system using only one DC/DC converter,
in this case, a Single Ended Primary Inductance Converter
(SEPIC), reducing hardware costs. As the input voltage of the
SEPIC can be higher or lower than the output voltage, this
converter presents obvious design advantages [4].
The input and output modules connected to the SEPIC
correctly changed using two switches controlled by the
microcontroller.
This paper is divided into six sections, as follows. Section 1
is the introduction. Section 2 presents the system architecture. Section 3 presents the charging controller and energy
management strategy. Section 4 presents high power LED
module and brightness control strategy. Section 5 shows solar
PV power LED lighting system characteristics. Section 6
shows experimental results. ending with conclusions presented in Section 7.
2. System Architecture
The proposed PV lighting system generates energy from sunlight by PV panel during the day, and illumination load only
works at night, and a battery is adopted for energy storage.
The most common battery type used is the valve regulated
lead-acid (VRLA), because of its low cost, maintenance-free
operation, and high efficiency characteristics [4, 13]. The
system also needs a long life and environmental illumination
source, and high power white LED fits well this demand.
ISRN Renewable Energy
Figure 1 shows the block diagram of the proposed lighting
system which is composed of a PV panel, a unique DC/DC
converter regulated by the electronic and microcontroller
module, a VRLA battery, and a high power white LED
array. The PV lighting system controller is used to achieve
battery charge regulation, to execute MPPT algorithm, and to
control brightness intensity. The DC/DC converter is used to
interface the PV panel to the battery using the two switches
(switch 1 and switch 2). The same DC/DC converter is also
used to provide the power to the high power white LED
array from the battery. An NTC sensor is used to measure
the battery temperature that is needed to battery charge
algorithm.
In PV lighting system, choosing the electronic components is very important for cost reduction, reliability, and
efficiency [2, 7]. PV panel and high power white LED array
are the most expensive components of the overall system, so
the microcontroller board should make full use of them.
3. Charging Controller and Energy
Management Strategy
A detailed block diagram of the charge regulation module is
shown in Figure 2 (similar to Figure 1 but with switches 1 and
2 connected as showed in Figure 2). The system consists of a
nonlinear current source, an SEPIC, a battery, and electronics
and the microcontroller board. The SEPIC is used to interface
PV to battery controlling its charge.
In this system, in order to save components and to
increase system efficiency, the power converter acts not only
as a maximum power point tracker but also as a charger
to manage the state-of-charge of the battery by regulating
the charging current or voltage. In this case, control of the
power converter is actually a multiobjective control problem.
Rather than being controlled to serve as a sole voltage or
current regulator, the power converter is required to regulate
and balance the power flow between the solar array and the
battery under different insolation and load conditions.
3.1. Charging Control Strategy. The complete battery charging
demands to the controller a complex control strategy, in
which it would be possible to charge the battery, between
its limits, in the faster possible way since working periods of
energy generation of the PV panel are limited [14]. To achieve
a fast, safe, and complete battery lead-acid charging process,
some of the manufacturers recommend dividing the charging
process in four stages [2, 3] that are designated by: (1∘ ) trickle
charge, (2∘ ) bulk charge, (3∘ ) over charge and (4∘ ) float charge
illustrated in Figure 3.
3.1.1. 1∘ Stage (from T0 to T1 )—Trickle Charge. This first stage
appears when the battery voltage is below the value 𝑉CHGENB
This voltage value, specified for the manufacturers, shows that
the battery arrives at its critical discharge capacity. In this
condition the battery should receive a small charge current
defined by 𝐼TC that has a typical value of 𝐶/100 where 𝐶 is
the normal battery capacity with a 10 hours charging process.
This small current 𝐼TC is applied until the battery voltage
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PLED
array
PV
panel
Switch 1
L1
Switch 2
D1
C2
Battery
C1
M1 L 2
PV panel voltage
and current sensing PWM signal
C3
Battery voltage
supervision
Power LEDs voltage
and current sensing
Microcontroller
PV and battery charge with PWM duty
cycle adjustment
Power LED current control with PWM duty
cycle adjustment
Charge/light
function
signal
Battery
temperature
sensing
Charge/light
function
signal
Figure 1: Stand alone photovoltaic lighting block diagram (PWM used to define the duty cycle).
PV
panel
Switch 1
L1
C2
D1
Switch 2
Battery
C1
M1 L 2
C3
PV panel voltage
and current sensing PWM signal
Microcontroller
PV and battery charge with PWM
duty cycle adjustment
Charge
function
signal
Battery voltage
supervision
Battery
temperature
sensing
Charge
function
signal
Figure 2: Photovoltaic battery charging block diagram (PWM used to define the duty cycle).
IBULK
Battery current
IOCT
ITC
reaches the value of 𝑉CHGENB . This stage also avoids that
some accident could happen in the case when the one battery
element is in curt circuit; therefore if this really happens the
battery voltage will not grow and then the battery charging
process does not pass for the next stage.
ISTEADY
2∘
stage
1∘
stage
3∘
stage
4∘
stage
VOC
VFLOAT
Battery output voltage
VCHGENB
T0
T1
T2
T3
Figure 3: Current and voltage curves in the four stages of battery
charging.
3.1.2. 2∘ Stage (from T1 to T2 )—Bulk Charge. After the battery
voltage reaches the value 𝑉CHGENB it delivers to the battery
a constant current 𝐼BULK . The 𝐼BULK is the maximum charge
current that battery supports without a big water losing, and
its value is specified by the manufacturers. This current is
applied until the battery voltage reaches the maximum value
of overcharge voltage, defined by 𝑉OC and specified by the
manufacturers.
3.1.3. 3∘ Stage (from T2 to T3 )—Overcharge. During this stage
the control algorithm should regulate the battery voltage in
the 𝑉OC so that the complete charge has been reached. When
the charging current falls down to a preestablished value 𝐼OTC
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Start BOCH
PV/battery
Read Vb IPV and Tb
Yes
Vb ≥ VOC (Tb )
R0
R1
R3 Battery/
PLED lighter
SEPIC
DC/DC
converter
R2
R5
R4
No
Figure 5: Voltage and current sensors for battery charging algorithm and voltage and current sensor for LED lighting current
control.
PWM = PWM old − K
Start P and O
Execute MPPT
P and O algorithm
Read VPV and IPV
IPV ≤ ISTEADY
Yes
PPV = VPV ∗IPV
No
ΔPPV = PPV − PPV old
PWM = 0
ΔPWM =
PWM − PWM old
Return to start BOCH
Yes
Figure 4: Battery charging algorithm with two main stages (bulk
and overcharge (BOCH) stages) (PWM used to define the duty
cycle).
ΔPPV ≥ 0
ΔPWM ≥ 0
and the voltage stays in the value 𝑉OC , the next stage will be
executed. The value of 𝐼OCT is around 10% of the 𝐼BULK .
3.1.4. 4∘ Stage (from T3 until the End)—Float Charge. In this
stage the control algorithm will apply in the battery a constant
voltage 𝑉FLOAT which is a specified value by the battery
manufacturers. This voltage is applied to the battery with the
objective to avoid its auto-discharge. During the discharging
process the battery voltage will fall down and when it achieves
0.9 𝑉FLOAT the control algorithm will execute again the 2∘
stage providing the 𝐼BULK current. The control algorithm only
returns to the 2∘ stage if the PV panel is producing energy, if
not the battery will continue the discharge process that could
reach a voltage below the value 𝑉CHGENB ; in this situation the
control algorithm should restart the charging process in 1∘
stage when the PV panel will have energy again.
In this work there are some simplifications made in the
implementation of the four different charging stages of a leadacid battery. The 1∘ stage was not implemented because the
discharge battery with this prototype board does not pass
below 𝑉FLOAT (minimum lowest security voltage specified by
the battery manufacturers). In this situation the applied load
is disconnected from the battery by the control algorithm
to avoid reaching critical discharge. The value of 𝑉FLOAT
depends onor is a function of the battery temperature. The
4∘ stage was not implemented but the 3∘ stage is continued
until the charge current reaches 𝐼STEADY (10% of 𝐼BULK ) and
finally the charging process is ended. When the PV panel has
energy to deliver and the battery voltage is below the 𝑉OC the
control algorithm executes the 2∘ stage. The battery charging
algorithm implemented in this work can be seen in Figure 4.
Yes
PWM =
PWM old + K
No
ΔPWM ≥ 0
No
No
PWM =
PWM =
PWM old − K PWM old + K
Yes
PWM =
PWM old − K
Return to start P and O
Figure 6: P&O MPPT algorithm (PWM used to define the duty
cycle applied in the MOSFET gate).
The parameter 𝐾 is the step given to the duty cycle of the
PWM signal. 𝑉𝑏 and 𝐼PV are the battery voltage and delivered
current from PV panel and 𝑇𝑏 is the battery temperature.
The maximum value of the 𝑉OC depends on the battery
temperature 𝑉OC (𝑇𝑏 ). From Figure 4 it is clear that only the
2∘ and the 3∘ stages are implemented from the four stages
proposed in [2, 3].
In the 2∘ stage of the battery charge, the use of an MPPT
algorithm is very important to maximize the absorbed PV
panel energy reducing the PV power needed. The correct
choice of the PV panel power should guarantee that the 𝐼BULK
is never overcome.
3.2. MPPT Algorithm. The P&O is one of the so called “hillclimbing” MPPT methods, which is based on the VoltagePower (𝑉-𝑃) of the PV characteristic curve [15], on the left
side of the hill of the 𝑉-𝑃 curve, the variation of the power
is positive when d𝑃/d𝑉 > 0, at the right side is negative
d𝑃/d𝑉 < 0. If the operating voltage of the PV panel is
perturbed in a given direction and d𝑃/d𝑉 > 0, it is known that
the perturbation moved the panel’s operating point toward
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PLED
array
Switch 1
L1
Switch 2
D1
C2
Battery
C1
Battery voltage
supervision
M1 L 2
PWM signal
C3
Power LEDs voltage
and current sensing
Microcontroller
Power LED current control with PWM duty
cycle adjustment
Charge/light
function
signal
Battery
temperature
sensing
Charge/light
function
signal
Figure 7: Power LED lighting block diagram (PWM used to define the duty cycle).
Start PI and OV control
Read VPLED and IPLED
+
EPLED = IDPLED − IPLED
−
.
..
.
..
Yes
.
..
VPLED < VMAXPLED
PWM = PWM old +
KP ∗ EPLED
Current control
Figure 8: PLED array.
IDPLED
+
EPLED
−
PI
controller
algorithm
PWM
SEPIC
connected to
power LED
array
No
PWM = PWM old − 1
Limited current control
Return to start PI and OV control
IPLED
Figure 9: Block diagram of the PLED current controller (PWM used
to define the duty cycle).
the MPP. The P&O algorithm would then continue to perturb
the PV panel voltage in the same direction. If d𝑃/d𝑉 < 0,
then the perturbation in operating point moved the PV panel
away from the MPP, and the P&O algorithm reverses the
direction of the perturbation [16]. The main advantage of the
P&O method is that it is easy to implement, and it has low
computational demand. However, it has some limitations, like
oscillations around the MPP in steady state operation, slow
response speed, and tracking in wrong way under rapidly
Figure 10: PLEDs PI current control and overvoltage supervision
algorithm (PWM used to define the duty cycle).
changing in sun radiations or the appearing of shadows [2,
16, 17]. To reduce the presented limitations it will be useful to
use a small sampling period. The used sampling period is 200
milliseconds.
Using the SEPIC with current and voltage resistor sensors
illustrated in Figure 5, the P&O MPPT algorithm was implemented with some improvements. The MPPT algorithm
needs only the PV voltage and current information, and the
battery voltage information is needed to control the battery
charging and monitor its discharge.
𝑅0 = 𝑅5 and respective 𝑉𝑅0 are 𝑉𝑅5 are the voltages
used to measure input and output SEPIC currents 𝐼PV and
𝐼LED . 𝑅1 = 𝑅3 , 𝑅2 = 𝑅4 , and its voltages are used to
measure input and output SEPIC voltages 𝑉PV and 𝑉BAT .
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good working battery periods will be smaller than the ones
achieved without these deep discharges.
The microcontroller supervises the battery voltage and
when the battery voltage goes below a certain value, which
means that its level of discharge is big, the battery is disconnected from the power LED load by the microcontroller
with switch 2. To make these switches (switch 1 and switch
2) there are two P channel MOSFETs driven with electronics
and controlled by the microcontroller.
Next day, after a new charge period, the battery could be
connected again to the power LED lighting array.
The advantages of the proposed improvements are (a)
better exploitation of the power produced by the PV power
source (b) increased battery lifetime by restoring the maximum possible energy in battery in the shortest time possible.
Figure 11: Photo of the prototype electronic board.
4. High Power LED Module and
Brightness Control
The PV lighting system uses high power white LEDs and
the same SEPIC used in charging algorithm. This SEPIC is
projected to fit specific requirements such as high efficiency,
long service-lift, and reduced size. The circuit components
can provide a steadyand high efficiency (typically greater than
85%) operation state for the 19 W high power LED array used
in the PV lighting system. A detailed block diagram of the
current LED controller is showed in Figure 7. The SEPIC
is designed according to the system power requirements. It
can supply a maximum output current of 4.0 Ampere to
drive the LED array. With overvoltage protection and output
current control feedback it is able to maintain a constant LED
brightness.
Figure 12: Photo of the stand alone photovoltaic lighting prototype.
The microcontroller uses 6 analogue-to-digital (A/D) converters with 10 bits and with one fast mode PWM signal to
control the lighting system. The period of the PWM signal is
100 KHz.
The flow chart of the implemented P&O MPPT algorithm
is illustrated in Figure 6.
The parameter 𝐾 is the step given to the duty cycle of the
PWM signal. This parameter is a function of the working
point of the DC/DC converter, linear or nonlinear region. The
𝐾 parameter is inverse proportional to the current absorbed
from the PV panel to get fast convergence to the MPP
tracker. It is expected that this algorithm shows some inherent
oscillation around the MPP [7].
3.3. Discharge Monitoring. In the developed prototype the
algorithm also supervises the battery discharge because,
for correct working periods of the lead-acid battery its
voltage cannot go below a certain value established by the
manufacture. If the discharge goes deep several times the
4.1. Power LED Lighting System. The power LEDs used to
make the lighting system are white with 3.2 and 400 mA each
to give the maximum brightness at low working temperature.
The number of PLEDs used to make the PLED lighting system
is chosen to achieve a desired brightness.
There are 15 PLEDs, 3 frames in parallel of 7 PLEDs
each, connected in series, as illustrated in Figure 8. The PLED
lighting system will consume about 19 W of power working at
maximum brightness that the PLED can give.
The system has a real-time clock (RTC) to control the
illumination time; it turns on when night comes and turns
off around 12 p.m. or another programed hour every day if
battery has enough power.
To reduce the PLED lighting brightness variations with
temperature changes, the PLEDs need an efficient dissipation
material behind them to avoid the overheating of the LEDs
providing a low temperature working point. The prototype
of the LED lighting systems has 15 power LED with a large
dissipation metal area. The PLEDs are from OSRAM.
A lens is used to focus the PLED brightness to the floor
making a desired illumination area in the floor.
4.2. PI Current Control Algorithm. The brightness of the proposed lighting system is defined measuring and controlling
the current in the PLED array. When the lighting system
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Battery charging 17/03/2013 (MPPT-2∘ stage)
45
1.2
40
1
35
30
0.8
25
0.6
20
15
0.4
10
0.2
5
6:50
7:09
7:29
7:49
8:09
8:29
8:50
9:10
9:31
9:52
10:13
10:34
10:55
11:17
11:38
11:59
12:21
12:42
13:03
13:25
13:46
14:07
14:29
14:50
15:12
15:33
15:54
16:16
16:37
16:58
17:20
17:42
18:03
18:25
18:47
19:09
19:31
19:52
0
VBAT [V] left yy axis
PPV [W] left yy axis
0
VPV [V] left yy axis
IPV [A] right yy axis
Figure 13: Part of the bulk charging phase of the battery charging process results.
45
Battery charging 18/03/2013 (MPPT 2∘ stage and overcharge-3∘ stage)
40
1.2
1
35
30
0.8
25
0.6
20
15
0.4
10
0.2
5
0
6:50
7:09
7:29
7:49
8:09
8:29
8:50
9:10
9:31
9:52
10:13
10:34
10:55
11:17
11:38
11:59
12:21
12:42
13:03
13:25
13:46
14:07
14:29
14:50
15:12
15:33
15:54
16:16
16:37
16:58
17:20
17:42
18:03
18:25
18:47
19:09
19:31
19:52
0
VBAT [V] left yy axis
VPV [V] left yy axis
PPV [W] left yy axis
IPV [A] right yy axis
Figure 14: Part of the overcharging phase of the battery charging process results.
is turned on the current control algorithm uses a soft start
because the DC/DC does not work correctly with big current
transitions. After the soft start, the Proportional Integral (PI)
controller starts working adjusting the PWM signal to take
the current (𝐼PLED ) to the desired current (𝐼DPLED ) forcing a
zero error (𝐸PLED ) as illustrated in block diagram of Figure 9.
The proposed current control is a simplify proportional
on and Integral controller based
PWM = PWM− old + 𝐾𝑃 ∗ 𝐸PLED ,
(1)
where the PWM is the control signal applied in the SEPIC
MOSFET, PWM old is the previous control signal applied,
𝐸PLED is the error between the desired and real currents and
𝐾𝑃 is a gain. A sampling period of 200 milliseconds is used.
The proposed lighting system turns on when night comes
or it is too dark and turns off at a programmed hour
(p.e. 00:00). The proposed lighting system will be used in
public park illumination and after that hour there is no need
to be turned on.
The current controller algorithm also supervises the output PLEDs voltage array to detect an open LED frame or an
overvoltage hardware error situation.
The algorithm measures the PLED array voltage (𝑉PLED ),
and knowing the maximum security voltage (𝑉MAXPLED ), if
the PLED array voltage is smaller than the maximum PLED
array voltage, it runs the simplified PI control algorithm and
if it is bigger, it limits the applied current as can be seen in
Figure 10.
The lighting PLED system algorithm achieved good
current control results even with battery voltage variation
caused by the different battery levels of charge.
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PLED lighting 18/03/2013 (current control)
25
2
1.8
20
1.6
1.4
15
1.2
1
10
0.8
0.6
5
0.4
0.2
20:11
20:27
20:44
21:01
21:18
21:35
21:52
22:09
22:26
22:43
23:00
23:17
23:34
23:51
0:08
0:24
0:41
0:57
1:14
1:30
1:46
2:03
2:19
2:36
2:52
3:09
3:25
3:42
3:58
4:14
4:31
4:47
5:04
5:20
5:37
5:53
6:09
6:26
0
VBAT [V] left yy axis
PLED [W] left yy axis
0
VPV [V] left yy axis
ILED [A] right yy axis
Figure 15: Current control results during night.
Charged and consumed energy 17, 18/03/2013 (Wh)-24 h
200
180
160
140
120
100
80
60
40
0
6:50
7:24
7:59
8:35
9:11
9:47
10:24
11:02
11:39
12:17
12:54
13:31
14:09
14:46
15:24
16:01
16:39
17:17
17:55
18:33
19:11
19:49
20:25
21:02
21:39
22:17
22:54
23:31
0:08
0:44
1:20
1:56
2:33
3:09
3:45
4:21
4:57
5:33
6:09
20
Charged and consumed energy (Wh)
Figure 16: Charged and consumed accumulated energy during 24 hours (from the 190 Wh given by the PV panel during day 85% are
accumulated (161 Wh)) and 78 Wh of consumed energy during night.
5. Solar PV Power LED Lighting
System Characteristics
The practical experimental PV lighting system consists of a
30 W PV panel, 12 V 20 Ah VRLA CSB battery, a 19 W high
white PLED array, and the microcontroller board with the
necessary electronics.
It is used a 30 Watt PV panel with a 𝑉PP = 30 Volt and
𝐼PP = 1 Ampere
The VRLA battery has 12 V/20 Ah. The maximum charge
current 𝐼BULK should be 10% of 20 Ah, with a maximum
current that comes from the PV panel of 2.0 Ampere the latest
condition is always verified. It is also important that battery
has enough capacity to maintain the system working even in
periods without charge (shadow or rainy days).
The power LED characteristics are 3.2 V and 400 mA for
the maximum brightness. To have a lighting system with the
desired brightness there are 15 PLEDs, 3 frames in parallel
of 5 PLEDs each connected in series consuming about 19 W
(16.0 V and 1.2 Amp).
The microcontroller is an ATTINY861V of the ATMEGA
family that runs the two main algorithms: charge and
supervise discharge algorithm and PLED current control
algorithm. The microcontroller always supervises the PV
voltage and current; if 𝑉PV is bigger than 14.0 V and 𝐼PV is near
zero Ampere, the proposed lighting system starts the charge
and monitor discharge algorithm, described in Section 3.
When 𝐼PV is near zero Ampere and 𝑉PV is below 14.0 V the
proposed system starts the PLED current control algorithm.
The implemented prototype electronic board with SEPIC,
microcontroller, and the necessary electronics components is
illustrated in Figure 11.
In the right side of the board, the PV panel input connection (𝑀) can be seen and in the left side the connection to
ISRN Renewable Energy
the battery output/input connection (𝐵) and the load output
connection (𝐿) that connects to the power LED lighting
system. In the right side down there is the NTC temperature
connection sensor to monitor the battery temperature.
Figure 12 shows the prototype of the stand alone photovoltaic lighting system installed in a public park in Lisbon,
Portugal.
6. Experimental Results
In Figure 13, part the bulk charging phase of the batterycharging process for a 30 W nominal power PV source is
shown. During this phase, the maximum available PV power
is transferred to the battery stack, according to the MPPT
algorithm.
In Figure 14, part of the overcharge phase is initiated when
the battery voltage rises to 14.6 V and the battery charging
current is progressively reduced to 0.1 Amp at the end of
this phase. At the end of the this phase, the battery is left in
open-circuit condition and the battery voltage measured after
20 h was found to be 12.9 V, corresponding to 100% battery
state of charge, thus proving the success of the charging
algorithm.
Figure 15 shows the current control process where the
system continuously works all night, the current is controlled
to remain stable at a value of 1.2 Ampere to give a constant
brightness. The error range was controlled in ±0.08 Ampere
to meet the actual demand. The LED lighting system is
disconnected at 00:00 by the microcontroller.
Figure 16 shows the charged and consumed energy for the
example day (a sunny day 18/03/2013). As can be seen the
accumulated energy is approximated twice of the consumed
energy. This fact is important to have the battery almost
allways charged and in shadow days at night the lighting
system also works using the stored energy.
7. Conclusions
This work presents an improved PV lighting system with
MPPT, battery charger, high power White LEDs, and selfadapting brightness control. The microcontroller based on
ATMEGA (ATTINY861V) is used to implement the system control in different operating states, including MPPT,
charging, and lighting. In charging circuit, improvements
in Perturbs & Observed MPPT method for PV array and
improvements in charging strategy for VRLA battery are
implemented; in lighting circuit, 19 W high power white LED
array and it is lighting power module can work in a highefficiency state; self-adapting current control for maintaining
a constant brightness is implemented. Experimental results
also verify the performance of the proposed photovoltaic
lighting system and its energy balance. The proposed stand
alone public lighting system presented several improvements
like the use of only one DC/DC converter and a real-time
clock that can be used to save energy or reduce the brightness
after a predefined hour.
9
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